990f4e2919
* Implement reshapeable CTCGreedyDecoderPlusSparseToDense transformation and test Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com> * Fix consts (after code-review #1) Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com> * Add CTCGreedyDecoderTransformation with more generic pattern Also it adds new middle-replacer for transforming sequence length to a mask along with tests. Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com> * Do fixes after review #2 Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com> * Fix after review #3 Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com> * Fix after review #4 Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
68 lines
3.4 KiB
Python
68 lines
3.4 KiB
Python
"""
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Copyright (C) 2020 Intel Corporation
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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"""
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import unittest
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import numpy as np
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from extensions.middle.SequenceLengthToMask import SequenceLengthToMask
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from mo.front.common.partial_infer.utils import int64_array
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from mo.utils.ir_engine.compare_graphs import compare_graphs
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from mo.utils.unittest.graph import build_graph
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nodes_attributes = {'logits': {'shape': int64_array([5, 3, 30]), 'type': 'Parameter', 'kind': 'op',
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'op': 'Parameter'},
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'logits_data': {'value': None, 'shape': int64_array([5, 3, 30]), 'kind': 'data'},
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'seq_length': {'type': 'Const', 'kind': 'op', 'op': 'Const', 'value': int64_array([5, 2, 3])},
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'seq_length_data': {'value': int64_array([5, 2, 3]), 'kind': 'data'},
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'ctc_greedy_decoder': {'type': None, 'kind': 'op', 'op': 'CTCGreedyDecoder',
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'use_mask_format': True},
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'ctc_greedy_decoder_data': {'value': None, 'shape': None, 'kind': 'data'},
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'last': {'kind': 'op', 'op': 'Result'},
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# new nodes
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'seq_mask': {'type': 'Const', 'kind': 'op', 'op': 'Const',
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'value': np.transpose(np.array([[1, 1, 1, 1, 1],
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[1, 1, 0, 0, 0],
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[1, 1, 1, 0, 0]], dtype=np.float))},
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'seq_mask_data': {'value': None, 'kind': 'data'},
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'new_ctc_greedy_decoder': {'type': None, 'kind': 'op', 'op': 'CTCGreedyDecoder'},
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}
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class ScaleInputTests(unittest.TestCase):
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def test1(self):
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graph = build_graph(nodes_attributes,
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[('logits', 'logits_data'),
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('logits_data', 'ctc_greedy_decoder'),
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('seq_length', 'seq_length_data'),
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('seq_length_data', 'ctc_greedy_decoder'),
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('ctc_greedy_decoder', 'ctc_greedy_decoder_data'),
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('ctc_greedy_decoder_data', 'last')],
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nodes_with_edges_only=True)
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graph_ref = build_graph(nodes_attributes,
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[('logits', 'logits_data'),
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('logits_data', 'new_ctc_greedy_decoder'),
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('seq_mask', 'seq_mask_data'),
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('seq_mask_data', 'new_ctc_greedy_decoder'),
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('new_ctc_greedy_decoder', 'ctc_greedy_decoder_data'),
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('ctc_greedy_decoder_data', 'last')],
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nodes_with_edges_only=True)
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SequenceLengthToMask().find_and_replace_pattern(graph)
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(flag, resp) = compare_graphs(graph, graph_ref, 'last')
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self.assertTrue(flag, resp)
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